Aashna Uppal
DPhil Student
I am thrilled to be here as part of the HDRUK-Turing-Wellcome PhD Programme in Health Data Science. Before coming to the University of Oxford, I worked as an epidemiologist at the Public Health Agency of Canada, on a COVID-19 surveillance and epidemiology team. My academic background is in biology and mathematics (undergraduate) and public health (graduate) – I’ve completed both my BSc and MScPH at McGill University in Montreal, Canada. During that time, I had the opportunity to work with a research team focused on answering a variety of questions related to tuberculosis in the Canadian North. We used methods like dynamic infectious disease modelling and cost-effectiveness analysis. Despite living in Montreal for six years, my French is incredibly mediocre, but I consider myself to be fluent in “franglais”! When I’m not at the Big Data Institute (or, equivalently, huffing and puffing while cycling up Headington Hill), I enjoy baking and watching Bollywood movies.
Recent publications
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Using a Machine Learning Approach to Predict Snakebite Envenoming Outcomes Among Patients Attending the Snakebite Treatment and Research Hospital in Kaltungo, Northeastern Nigeria
Hamman NA. et al, (2025), Tropical Medicine and Infectious Disease, 10, 103 - 103
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Epidemiology of Paediatric Snakebites in Northeastern Nigeria: A Retrospective Single-Center Study
Hamman NA. et al, (2025)
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Using a Machine Learning Approach to Predict Snakebite Envenoming Outcomes Among Patients Attending the Snakebite Treatment and Research Hospital Kaltungo, Northeastern Nigeria
Hamman NA. et al, (2025)
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Corrigendum to "No evidence of difference in mortality with amoxicillin versus co-amoxiclav for hospital treatment of community-acquired pneumonia" [J Infect 88 (2024) 106161].
Wei J. et al, (2024), The Journal of infection, 89
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Prevalence of undiagnosed hypertension and associated factors in Ndera sector, Gasabo district of Rwanda: a cross-sectional study.
Okesina AA. et al, (2024), BMC public health, 24